AUTHOR=Wang Yutao , Yan Kexin , Lin Jiaxing , Li Jun , Bi Jianbin 

TITLE=Macrophage M2 Co-expression Factors Correlate With the Immune Microenvironment and Predict Outcome of Renal Clear Cell Carcinoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.615655

DOI=10.3389/fgene.2021.615655

ISSN=1664-8021

ABSTRACT=Abstract

Purpose: 
In the tumor microenvironment, the functional differences among various tumor-associated macrophages (TAM) are not completely clear. Tumor-associated macrophages are thought to promote the progression of cancer. This article focuses on exploring M2 macrophage-related factors and behavior of renal clear cell carcinoma.  
Method: We obtained a renal clear cell carcinoma data matrix from TCGA-KIRC-FPKM, and GSE8050, GSE12606, GSE14762, GSE36895, and GSE46699. We used the ‘Cibersort’ algorithm to calculate type M2 macrophage proportions among 22 type immune cells. M2 macrophage-related co-expression module genes were selected using weighted gene co-expression network analysis （WGCNA）. A renal clear cell carcinoma prognosis risk score was built based on M2 macrophage-related factors. ROC curve and Kaplan–Meier analysis were performed to evacuate the risk score in various subgroups. The Pearson test was used to calculate correlations among M2 macrophage-related genes, clinical phenotype, immune phenotype and tumor mutation burden (TMB). The human protein atlas (HPA) database was used to show the difference of the co-expression genes at the protein level.
Results: Six M2 macrophage co-expressed genes (F13A1, FUCA1, SDCBP, VSIG4, HLA-E, TAP2) positively related to infiltration of M2 macrophages; these were enriched in the neutrophil activation involved in immune response and antigen processing and presentation of exogenous peptide antigen via MHC class I. M2-related factors frequency were robust biomarkers for predicting the renal clear cell carcinoma patient clinical phenotype and immune microenvironment. The Cox regression model built based on M2 macrophage-related factors showed a close prognosis correlation (AUC = 0.78). Proteins encoded by these genes (F13A1, FUCA1, SDCBP, VSIG4, HLA-E, TAP2) varied among tumor groups and normal tissue by immunohistochemistry, which suggested the clinical phenotype correlation at both the mRNA and protein levels.
Conclusion: These co-expressed genes were the most M2 macrophage-related factors. They correlated with immune microenvironment and predicted outcome of renal clear cell carcinoma. These co-expression genes and the biological processes involved with them might provide new strategies for intervention via chemotaxis of M2 macrophages.